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Caroline M. Hermans and Jon D. Erickson
Environmental decision making involving multiple stakeholders can benefit from the use of a formal process to structure stakeholder interactions, leading to more successful…
Abstract
Environmental decision making involving multiple stakeholders can benefit from the use of a formal process to structure stakeholder interactions, leading to more successful outcomes than traditional discursive decision processes. There are many tools available to handle complex decision making. Here we illustrate the use of a multicriteria decision analysis (MCDA) outranking tool (PROMETHEE) to facilitate decision making at the watershed scale, involving multiple stakeholders, multiple criteria, and multiple objectives. We compare various MCDA methods and their theoretical underpinnings, examining methods that most realistically model complex decision problems in ways that are understandable and transparent to stakeholders.
Rojas-Trejos Carlos Alberto and González-Velasco Julián
Waste production is one of the most important problems that humankind faces. Human-based activities generate diverse waste types that have to be treated and disposed differently…
Abstract
Waste production is one of the most important problems that humankind faces. Human-based activities generate diverse waste types that have to be treated and disposed differently. This results in the need to build more facilities to manage the waste and to avoid further environmental damage. Colombia established a successful policy to close open dumps and to control pollution. Notwithstanding the advances that have been made in final disposal, it is necessary to extend the life of the final disposal sites and increase the closure of open landfills. Valle del Cauca is the third most populated Colombian province, and it is also considered the third province that generates more waste. This chapter addresses the problem of locating solid waste disposal centers in Valle del Cauca by applying the analytic hierarchy process (AHP) with fuzzy logic, a multicriteria method that compares opinions of a decision-making group. Additionally, each potential location area is characterized by considering industrial and environmental issues, societal dynamics, infrastructure and topography, costs, and taxes. After applying a variant of AHP, the decision-making group was able to find that Jamundi is the best location to open the disposal center. The method shows strong potential to identify and prioritize alternative locations for a diverse group of stakeholders. Most importantly, the methodology lets us structure better qualitative and quantitative data, as well as to link multiple levels to avoid choosing locations that will affect society, environment, and other stakeholders, without considering the trade-offs among diverse criteria considering benefits, opportunities, costs, and risks (BOCR).
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This chapter presents the survey of selected linear and mixed integer programming multi-objective portfolio optimization. The definitions of selected percentile risk measures are…
Abstract
This chapter presents the survey of selected linear and mixed integer programming multi-objective portfolio optimization. The definitions of selected percentile risk measures are presented. Some contrasts and similarities of the different types of portfolio formulations are drawn out. The survey of multi-criteria methods devoted to portfolio optimization such as weighting approach, lexicographic approach, and reference point method is also presented. This survey presents the nature of the multi-objective portfolio problems focuses on a compromise between the construction of objectives, constraints, and decision variables in a portfolio and the problem complexity of the implemented mathematical models. There is always a trade-off between computational time and the size of an input data, as well as the type of mathematical programming formulation with linear and/or mixed integer variables.
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In this chapter, the integrative methodological approach (IMA) of the research project GLOWA Elbe is introduced, which represents a scientific methodology to support water…
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In this chapter, the integrative methodological approach (IMA) of the research project GLOWA Elbe is introduced, which represents a scientific methodology to support water management under uncertainty regarding future paths of global change. The approach paves the way for integration of research work of many disciplines, of different assessment methods, of various policy fields, and the involvement of relevant stakeholders and decision makers. IMA can be roughly described by four research elements (scenario derivation, indicator and criteria identification, model-based impact analysis, and final scenario assessment based on combined benefit–cost and multi-criteria analysis), which lay the basis for the IMA activities of the global change research sequence. Its practical application is demonstrated by a case study on the Spree and Schwarze Elster river basins. Specific results of Chapter 4 (on scenario derivation) and Chapter 11 (on integrating economic evaluation into water management simulation) in this volume are picked up in order to focus on the illustration of the integrated assessment results for this German case study.
Georgiy Levchuk, Daniel Serfaty and Krishna R. Pattipati
Over the past few years, mathematical and computational models of organizations have attracted a great deal of interest in various fields of scientific research (see Lin & Carley…
Abstract
Over the past few years, mathematical and computational models of organizations have attracted a great deal of interest in various fields of scientific research (see Lin & Carley, 1993 for review). The mathematical models have focused on the problem of quantifying the structural (mis)match between organizations and their tasks. The notion of structural congruence has been generalized from the problem of optimizing distributed decision-making in structured decision networks (Pete, Pattipati, Levchuk, & Kleinman, 1998) to the multi-objective optimization problem of designing optimal organizational structures to complete a mission, while minimizing a set of criteria (Levchuk, Pattipati, Curry, & Shakeri, 1996, 1997, 1998). As computational models of decision-making in organizations began to emerge (see Carley & Svoboda, 1996; Carley, 1998; Vincke, 1992), the study of social networks (SSN) continued to focus on examining a network structure and its impact on individual, group, and organizational behavior (Wellman & Berkowitz, 1988). Most models, developed under the SSN, combined formal and informal structures when representing organizations as architectures (e.g., see Levitt et al., 1994; Carley & Svoboda, 1996). In addition, a large number of measures of structure and of the individual positions within the structure have been developed (Roberts, 1979; Scott, 1981; Wasserman & Faust, 1994; Wellman, 1991).
Robert Gannon, Karen M. Hogan and Gerard T. Olson
New Technology Business Firms are known to be volatile dynamic organizations whose innovations are subject to short life cycles and product imitability. Venture capitalist firms…
Abstract
New Technology Business Firms are known to be volatile dynamic organizations whose innovations are subject to short life cycles and product imitability. Venture capitalist firms who allocate funds to these start-ups need to evaluate multiple facets associated with the individual firm’s internal and external characteristics, as well as, its own unique objectives and goals. This study applies a multicriteria decision making model to the identification for venture capital firms of potential New Technology Business Firms who are requesting capital infusions.
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The purpose of this paper is to introduce a new forecasting approach that involves a multicriteria scoring model, which is enhanced with regression analysis and optimization. We…
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The purpose of this paper is to introduce a new forecasting approach that involves a multicriteria scoring model, which is enhanced with regression analysis and optimization. We compare regression analysis versus our Enhanced Multicriteria Scoring Model by comparing the Error Sum of the Squares in case studies involving top selling automobiles and top Fortune 500 companies. In both the automobile and Fortune 500 case studies, our Enhanced Multicriteria Scoring was more accurate than regression analysis. In practice, our Enhanced Multicriteria Scoring Model should be compared with regression analysis, and the better of the two techniques should be used to forecast. In short, our Enhanced Multicriteria Scoring model is a “breakthrough” modeling technique that will help companies and organizations improve their forecasting.
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